In this competing renewal, a macro-simulation model, known as SimSmoke, will be expanded and improved. SimSmoke is designed to predict smoking prevalence and smoking-attributable deaths over time at the population level and to examine the effects of different public policies on these outcomes. The changes proposed are outlined in the following aims: (1) Extend the current SimSmoke work to better understand the relationship between smoking and lung cancer death rates. Analysis of this relationship will be improved by closer examination of exsmokers and age, gender, and racial/ethnic variations. The role of duration, quantity, and secondhand smoke also will be incorporated. (2) Expand the CISNET-I base case model beginning in 1975 to include background risks, tobacco control policies, secondhand smoke, and smoking intensity. Also, create a 25-year period over which to validate the tobacco control policy model by incorporating tobacco control policies beginning with the 1975 baseline. (3) Extend the model to consider the past and potential future role of telephone quitlines and the coordination of other smoking cessation strategies so that they are in line with current policy interests. (4) Model at least three states with the goal of making the model readily accessible for application to all states. Validate each of the state models in terms of its ability to predict smoking prevalence and lung-cancer-attributable deaths. (5) Complete a model of modified low-nitrosamine smokeless tobacco for use as an alternative (to cigarettes) nicotine delivery product. Develop and extend this prototype harm-reduction model to assess other alternative nicotine delivery products and to address regulatory issues that are relevant to policymakers. (6) Update the C++ model and the various Excel models to incorporate the most recent data available and to make them more readily available to the public. Continue to develop documentation for and improve the user-friendliness of both the Excel and C++ versions of the model and make them available on the web. (7) Critically examine the methods that are traditionally used to project lung cancer deaths and determine how the estimates depend on the sensitivity to key parameters.